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field_to_metadata_map={
'effect_maps': {'stat': 'effect'},
'variance_maps': {'stat': 'variance'},
'pvalue_maps': {'stat': 'p'},
'zscore_maps': {'stat': 'z'},
}),
name=f'collate_{level}_outputs')
ds_contrast_maps = pe.Node(
BIDSDataSink(base_directory=out_dir,
path_patterns=contrast_pattern),
run_without_submitting=True,
name='ds_{}_contrast_maps'.format(level))
ds_contrast_plots = pe.Node(
BIDSDataSink(base_directory=out_dir,
path_patterns=contrast_plot_pattern),
run_without_submitting=True,
name='ds_{}_contrast_plots'.format(level))
if ix == 0:
wf.connect([
(loader, select_entities, [('entities', 'inlist')]),
(select_entities, getter, [('out', 'entities')]),
(select_entities, ds_model_warnings, [('out', 'entities')]),
(select_entities, ds_design, [('out', 'entities')]),
(select_entities, ds_design_matrix, [('out', 'entities')]),
(plot_design, ds_design, [('figure', 'in_file')]),
(select_contrasts, plot_l1_contrast_matrix, [('out', 'contrast_info')]),
(select_contrasts, plot_corr, [('out', 'contrast_info')]),
(select_entities, ds_l1_contrasts, [('out', 'entities')]),
(select_entities, ds_corr, [('out', 'entities')]),
name='plot_corr')
plot_l1_contrast_matrix = pe.MapNode(
ContrastMatrixPlot(image_type='svg'),
iterfield=['data', 'contrast_info'],
name='plot_l1_contrast_matrix')
ds_design = pe.MapNode(
BIDSDataSink(base_directory=out_dir, fixed_entities={'suffix': 'design'},
path_patterns=image_pattern),
iterfield=['entities', 'in_file'],
run_without_submitting=True,
name='ds_design')
ds_design_matrix = pe.MapNode(
BIDSDataSink(base_directory=out_dir, fixed_entities={'suffix': 'design'},
path_patterns=design_matrix_pattern),
iterfield=['entities', 'in_file'],
run_without_submitting=True,
name='ds_design_matrix')
ds_corr = pe.MapNode(
BIDSDataSink(base_directory=out_dir, fixed_entities={'suffix': 'corr'},
path_patterns=image_pattern),
iterfield=['entities', 'in_file'],
run_without_submitting=True,
name='ds_corr')
ds_l1_contrasts = pe.MapNode(
BIDSDataSink(base_directory=out_dir, fixed_entities={'suffix': 'contrasts'},
path_patterns=image_pattern),
iterfield=['entities', 'in_file'],
'[sub-{subject}_][ses-{session}_]task-{task}[_acq-{acquisition}]' \
'[_rec-{reconstruction}][_run-{run}][_echo-{echo}][_space-{space}]_' \
'contrast-{contrast}_stat-{stat}_statmap.nii.gz'
# Set up general interfaces
#
# HTML snippets to be included directly in report, not
# saved as individual derivative files
#
reportlet_dir = Path(base_dir) / 'reportlets' / 'fitlins'
reportlet_dir.mkdir(parents=True, exist_ok=True)
snippet_pattern = '[sub-{subject}/][ses-{session}/][sub-{subject}_]' \
'[ses-{session}_]task-{task}_[run-{run}_]snippet.html'
ds_model_warnings = pe.MapNode(
BIDSDataSink(base_directory=str(reportlet_dir),
path_patterns=snippet_pattern),
iterfield=['entities', 'in_file'],
run_without_submitting=True,
name='ds_model_warning')
plot_design = pe.MapNode(
DesignPlot(image_type='svg'),
iterfield='data',
name='plot_design')
plot_corr = pe.MapNode(
DesignCorrelationPlot(image_type='svg'),
iterfield=['data', 'contrast_info'],
name='plot_corr')
plot_l1_contrast_matrix = pe.MapNode(